Diagnostic Evaluation of Rheumatoid Arthritis (RA) in Finger Joints Based on the Third-Order Simplified Spherical Harmonics (SP₃ ) Light Propagation Model

This work focuses on the evaluation of third-order simplified spherical harmonics (SP₃ ) model-based image reconstruction with respect to its clinical utility to diagnose rheumatoid arthritis (RA). The existing clinical data of 219 fingers was reconstructed for both absorption and scattering maps in fingers by using the reduced-Hessian sequential quadratic programming (rSQP) algorithm that employs the SP₃ model of light propagation. The k-fold cross validation method was used for feature extraction and classification of SP₃-based tomographic images. The performance of the SP₃ model was compared to the DE and ERT models with respect to diagnostic accuracy and computational efficiency. The results presented here show that the SP₃ model achieves clinically relevant sensitivity (88%) and specificity (93%) that compare favorably to the ERT while maintaining significant computational advantage over the ERT (i.e., the SP₃ model is 100 times faster than the ERT). Furthermore, it is also shown that the SP₃ is similar in speed but superior in diagnostic accuracy to the DE. Therefore, it is expected that the method presented here can greatly aid in the early diagnosis of RA with clinically relevant accuracy in near real-time at a clinical setting.